111 research outputs found
Rescoring Virtual Screening Results with the MM-PBSA Methods: Beware of Internal Dielectric Constants
With the potential of improving virtual screening outcome, MM-PB/GBSA has become a disputed method that requires extensive testing and tuning to provide the optimal results. One of the tuning factors is the internal or solute dielectric constant. We have applied three test sets with receptors of different categories and libraries from different sources to investigate the underlying issue related to this constant. We discovered that increasing internal dielectric value does not improve the virtual screening enrichment qualitatively. More interestingly, nonpolar and polar calculated energies act differently in libraries with different molecular weight distributions. From this work, the performance of MM-PBSA rescoring in virtual screening is more library- than receptor-dependent
Study of the interaction of Huperzia saururus Lycopodium alkaloids with the Acetylcholinesterase enzyme
In the present study, we describe and compare the binding modes of three Lycopodium alkaloids (sauroine, 6-hydroxylycopodine and sauroxine; isolated from Huperzia saururus) and huperzine A with the enzyme acetylcholinesterase. Refinement and rescoring of the docking poses (obtained with different programs) with an all atom force field helped to improve the quality of the protein?ligand complexes. Molecular dynamics simulations were performed to investigate the complexes and the alkaloid´s binding modes. The combination of the latter two methodologies indicated that binding in the active site is favored for the active compounds. On the other hand, similar binding energies in both the active and the peripheral sites were obtained for sauroine, thus explaining its experimentally determined lack of activity. MM-GBSA predicted the order of binding energies in agreement with the experimental IC50 valuesFil: Puiatti, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones En Fisico- Química de Córdoba. Universidad Nacional de Córdoba. Facultad de Cs.químicas. Instituto de Investigaciones En Fisico- Química de Córdoba; ArgentinaFil: Borioni, José Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones En Fisico- Química de Córdoba. Universidad Nacional de Córdoba. Facultad de Cs.químicas. Instituto de Investigaciones En Fisico- Química de Córdoba; ArgentinaFil: Vallejo, Mariana Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Cabrera, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Agnese, Mariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Ortega, María Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Pierini, Adriana Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones En Fisico- Química de Córdoba. Universidad Nacional de Córdoba. Facultad de Cs.químicas. Instituto de Investigaciones En Fisico- Química de Córdoba; Argentin
An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings
Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC \u3b2-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20 and 30%, compared to docking scoring or to standard MM-GBSA rescoring
計算機支援によるペプチド設計の理論と応用
学位の種別: 課程博士審査委員会委員 : (主査)東京大学客員准教授 富井 健太郎, 東京大学教授 菅野 純夫, 東京大学教授 浅井 潔, 東京大学准教授 木立 尚孝, 東京大学客員准教授 KamY. Zhang, 東京大学客員教授 泰地 真弘人University of Tokyo(東京大学
Advances and Challenges in Protein-Ligand Docking
Molecular docking is a widely-used computational tool for the study of molecular recognition, which aims to predict the binding mode and binding affinity of a complex formed by two or more constituent molecules with known structures. An important type of molecular docking is protein-ligand docking because of its therapeutic applications in modern structure-based drug design. Here, we review the recent advances of protein flexibility, ligand sampling, and scoring functions—the three important aspects in protein-ligand docking. Challenges and possible future directions are discussed in the Conclusion
Molecular dynamics and virtual screening approaches in drug discovery
Computer-aided drug discovery (CADD) methods are now routinely used in the
preclinical phase of drug development. Powerful high-performance computing
facilities and the extremely fast CADD methods constantly scale up the coverage of
drug-like chemical space achievable in rational drug development. In this thesis,
CADD approaches were applied to address several early-phase drug discovery
problems. Namely, small molecule binding site detection on a novel target protein,
virtual screening (VS) of molecular databases, and characterization of small
molecule interactions with metabolic enzymes were studied. Various CADD
methods, including molecular dynamics (MD) simulations in mixed solvents,
molecular docking, and binding free energy calculations, were employed. Co-solvent
MD simulations detected biologically relevant binding sites and provided guidance
for screening potential protein-protein interaction inhibitors for a crucial protein of
the SARS-CoV-2. VS with fragment- and negative image-based (F-NIB) models
identified three active and structurally novel inhibitors of the putative drug target
phosphodiesterase 10A. MD simulations and docking provided detailed insights on
the effects of active site structural flexibility and variation on the binding and
resultant metabolism of small molecules with the cytochrome P450 enzymes. The
results presented in this thesis contribute to the increasing evidence that supports
employment and further development of CADD approaches in drug discovery.
Ultimately, rational drug development coupled with CADD may enable higher
quality drug candidates to the human studies in the future, reducing the risk of
financially and temporally costly clinical failure.
KEYWORDS: Structure-based drug development, Computer-aided drug discovery
(CADD), Molecular dynamics (MD) simulation, Virtual screening (VS), Fragmentand
negative image-based (F-NIB) model, Structure-activity relationship (QSAR),
Cytochrome P450 ligand binding predictionMolekyylidynamiikka- ja virtuaaliseulontamenetelmät lääkeaine-etsinnässä
Tietokoneavusteista lääkeaine-etsintää käytetään nykyisin yleisesti prekliinisessä lääketutkimuksessa. Suurteholaskenta ja äärimmäisen nopeat tietokoneavusteiset lääkeaine-etsintämenetelmät mahdollistavat jatkuvasti kattavamman lääkkeenkaltaisten molekyylien kemiallisen avaruuden seulonnan. Tässä väitöskirjassa tietokonepohjaisia menetelmiä hyödynnettiin lääketutkimuksen prekliiniseen vaiheeseen liittyvissä tyypillisissä tutkimusongelmissa. Työhön kuului pienmolekyylien sitoutumisalueiden tunnistus uuden kohdeproteiinin rakenteesta, molekyylitietokantojen virtuaaliseulonta sekä pienmolekyylien ja metabolian entsyymien välisten vuorovaikutusten tietokonemallinnus. Työssä käytettiin useita tietokoneavusteisen lääkeaine-etsinnän menetelmiä, sisältäen molekyylidynamiikkasimulaatiot (MD-simulaatiot) vaihtuvissa liuottimissa, molekulaarisen telakoinnin ja sitoutumisenergian laskennan. Orgaanisen liuottimen ja veden sekoituksessa tehdyt MD-simulaatiot tunnistivat biologisesti merkittäviä sitoutumisalueita SARS-CoV-2:n tärkeästä proteiinista ja ohjasivat infektioon liittyvän proteiini-proteiinivuorovaikutuksen potentiaalisten estäjien etsintää. Virtuaaliseulonnalla tunnistettiin kolme rakenteellisesti uudenlaista tunnetun lääkekehityskohteen, fosfodiesteraasi 10A:n, estäjää hyödyntäen fragmentti- ja negatiivikuvamalleja. MD-simulaatiot ja telakointi tuottivat yksityiskohtaista tietoa sytokromi P450 entsyymien aktiivisen kohdan rakenteen jouston ja muutosten vaikutuksesta pienmolekyylien sitoutumiseen ja metaboliaan. Tämän väitöskirjan tulokset tukevat kasvavaa todistusaineistoa tietokoneavusteisen lääkeaine-etsinnän käytön ja kehityksen hyödyllisyydestä prekliinisessä lääketutkimuksessa. Tietokoneavusteinen lääkeaine-etsintä voi lopulta mahdollistaa korkeampilaatuisten lääkekandidaattien päätymisen ihmiskokeisiin, pienentäen taloudellisesti ja ajallisesti kalliin kliinisen tutkimuksen epäonnistumisen riskiä.
AVAINSANAT: Rakennepohjainen lääkeainekehitys, Tietokoneavusteinen lääkeaine-etsintä, Molekyylidynamiikkasimulaatio (MD-simulaatio), Virtuaaliseulonta, Fragmentti- ja negatiivikuvamalli, Rakenne-aktiivisuussuhde, Sytokromi P450 ligandien sitoutumisen ennustu
WISDOM: A Grid-Enabled Drug Discovery Initiative Against Malaria
The goal of this chapter is to present the WISDOM initiative, which is one of
the main accomplishments in the use of grids for biomedical sciences
achieved on grid infrastructures in Europe. Researchers in life sciences are
among the most active scientifi c communities on the EGEE infrastructure.
As a consequence, the biomedical virtual organization stands fourth in
terms of resources consumed in 2007, with an average of 7000 jobs submitted
every day to the grid and more than 4 million hours of CPU consumed in
the last 12 months. Only three experiments on the CERN Large Hadron
Collider have used more resources. Compared to particle physics, the use of
resources is much less centralized as about 40 different scientifi c applications
are now currently deployed on EGEE. Each of them requires an amount
of CPU which ranges from a few to a few hundred CPU years. Thanks to the
20,000 processors available to the users of the biomedical virtual organization,
crunching factors in the hundreds are witnessed routinely. Such
performances were already achieved on supercomputers but at the cost of
reservation and long delays in the access to resources. On the contrary, grid
infrastructures are constantly open to the user communities.
Such changes in the scale of the computing resources made continuously
available to the researchers in biomedical sciences open opportunities for
exploring new fi elds or changing the approach to existing challenges. In
this chapter, we would like to show the potential impact of grids in the fi eld
of drug discovery through the example of the WISDOM initiative
WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures
<p>Abstract</p> <p>Background</p> <p>Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the <it>Plasmodium </it>parasite, some are promising targets to carry out rational drug discovery.</p> <p>Motivation</p> <p>Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.</p> <p>Methods</p> <p>In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate <it>in silico </it>docking and in information technology to design and operate large scale grid infrastructures.</p> <p>Results</p> <p>On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, <it>In vitro </it>results are underway for all the targets against which screening is performed.</p> <p>Conclusion</p> <p>The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.</p
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